Apply python black style 🎱

Mamdasn · Dec 26, 2023 · 8f4fcc1 · 8f4fcc1
1 parent b9067db
commit 8f4fcc1
Show file tree

Hide file tree

Showing 2 changed files with 5 additions and 4 deletions.
diff --git a/code-example/showcase_video_im2dhisteq.py b/code-example/showcase_video_im2dhisteq.py
@@ -5,9 +5,7 @@
 cap = cv2.VideoCapture("assets/Arctic-Convoy-With-Giant-Mack-Trucks.mp4")
 
 # video without sound
-video_out_name = (
-    "assets/Arctic-Convoy-With-Giant-Mack-Trucks-im2dhisteq.mp4"
-)
+video_out_name = "assets/Arctic-Convoy-With-Giant-Mack-Trucks-im2dhisteq.mp4"
 
 i = 0
 j = 0

diff --git a/src/im2dhisteq.py b/src/im2dhisteq.py
@@ -3,6 +3,7 @@
 import numba
 import numpy as np
 
+
 @numba.njit()
 def transformer(image, w_neighboring=6):
     [h, w] = image.shape
@@ -22,6 +23,7 @@ def transformer(image, w_neighboring=6):
     CDFxn_transform = np.cumsum(X_transform)
     return CDFxn_transform, H_in
 
+
 @numba.njit()
 def im2dhisteq(image, w_neighboring=6):
     [h, w] = image.shape
@@ -30,11 +32,12 @@ def im2dhisteq(image, w_neighboring=6):
     bins = np.arange(256)
     # use linear interpolation of cdf to find new pixel values
     image_equalized = np.floor(
-        np.interp(V.flatten(), bins, 255*CDFxn_transform).reshape(h, w)
+        np.interp(V.flatten(), bins, 255 * CDFxn_transform).reshape(h, w)
     ).astype(np.uint8)
 
     return image_equalized
 
+
 @numba.njit()
 def vid2dhisteq(image, w_neighboring=6, Wout_list=np.zeros((10))):
     h, w = image.shape